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CAE-Test Correlation and CORA 30 Cases

30 Chapters
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01
CAE-Test Correlation Fundamentals: Aligning Simulation and Test Data
Establish a baseline correlation workflow by importing a CAE result and an experimental signal, aligning their time and amplitude axes, and computing a simple overlay to identify initial discrepancies.
CAE-TestCorrelation
02
Signal Preprocessing for Correlation: Filtering and Resampling Test Data
Apply appropriate low-pass filtering and resampling to experimental data to match the CAE output sampling rate, ensuring fair comparison and reducing noise artifacts before correlation metrics.
PreprocessingCorrelation
03
Time-Domain Correlation Metrics: Computing CORA Proximity Scores
Calculate CORA proximity scores for time-history curves using the standard CORA algorithm, interpret the sub-scores for phase, magnitude, and shape, and document the overall rating.
Time-DomainCorrelation
04
Frequency-Domain Correlation: Comparing Spectral Content
Perform FFT on both CAE and test signals, compute frequency-domain correlation metrics such as magnitude and phase coherence, and identify frequency bands with poor agreement.
Frequency-DomainCorrelation
05
Cross-Correlation for Time Lag Identification
Use cross-correlation to determine the time delay between CAE and test signals, quantify the lag, and adjust the CAE time base to improve alignment.
Cross-CorrelationIdentification
06
Modal Correlation: Comparing Mode Shapes and Frequencies
Extract modal parameters from test data and CAE results, compute Modal Assurance Criterion (MAC) values for mode shape pairs, and assess frequency errors.
CorrelationComparing
07
FRF Correlation: Validating Frequency Response Functions
Compare experimental and simulated FRFs using correlation metrics like FRAC and shape difference, and evaluate the quality of the correlation across frequency ranges.
FRFCorrelation
08
Nonlinear Correlation: Assessing Time-Domain Nonlinearities
Apply correlation techniques to nonlinear systems by comparing time histories under varying excitation levels, and use metrics that capture amplitude-dependent behavior.
NonlinearCorrelation
09
Uncertainty Quantification in Correlation: Propagating Test Variability
Incorporate measurement uncertainty into correlation analysis by performing Monte Carlo simulations on test data and computing confidence intervals for CORA scores.
UncertaintyQuantification
10
Sensitivity Analysis for Correlation Improvement
Identify which CAE model parameters most influence correlation scores by performing a sensitivity study, and prioritize parameters for calibration.
SensitivityAnalysis
11
Model Calibration Using Correlation Metrics as Objective
目标=Set up an optimization loop that adjusts CAE model parameters to maximize CORA scores, and validate the calibrated model against an independent test case.
CalibrationCorrelation
12
Correlation of Accelerometer Data: Handling Sensor Dynamics
Account for accelerometer frequency response and mounting effects in correlation by filtering CAE output with sensor transfer functions, and compare corrected signals.
CorrelationAccelerometer
13
Strain Gauge Correlation: Bridging Local Measurements and CAE
Correlate local strain measurements with CAE-predicted strains at corresponding locations, addressing issues of gauge length and orientation.
CorrelationBridging
14
Full-Field Correlation: Comparing DIC and CAE Displacement Fields
Use Digital Image Correlation (DIC) data to correlate full-field displacements with CAE results, computing field-level metrics such as grid point deviations.
Full-FieldCorrelation
15
Correlation for Durability: Time-Series Fatigue Damage Comparison
Compare fatigue damage computed from CAE and test time histories using a damage model, and correlate damage equivalent loads or cycles to failure.
CorrelationDurability
16
Correlation of Multi-Axis Vibration: Handling Multiple Inputs
Correlate CAE and test responses under multi-axis random vibration by computing coherence functions and principal component scores.
CorrelationMulti-Axis
17
Correlation of Transient Events: Shock and Impact
Correlate shock response spectra (SRS) from CAE and test for transient events, and evaluate peak acceleration and pulse duration errors.
CorrelationTransient
18
Correlation of Acoustic Data: Sound Pressure Level Comparison
Compare CAE-predicted sound pressure levels with microphone measurements using A-weighted levels and octave band correlation.
CorrelationAcoustic
19
Correlation of Thermal Data: Temperature History Matching
Correlate CAE thermal simulations with thermocouple measurements by comparing temperature histories and computing error metrics like RMSE and max deviation.
CorrelationTemperature
20
Correlation of Nonlinear Materials: Hyperelastic Model Validation
Validate a hyperelastic material model by correlating CAE force-displacement curves with test data from a tensile specimen, and adjust material parameters.
CorrelationNonlinear
21
Correlation of Contact Mechanics: Interface Stiffness Calibration
Correlate CAE contact models with test data from a contact stiffness experiment, and calibrate contact parameters to match the measured hysteresis.
CorrelationMechanics
22
Correlation of Composite Structures: Ply-Level Validation
Correlate CAE results with strain gauge data on a composite panel, focusing on ply-level strains and failure initiation.
CorrelationComposite
23
Correlation of Welded Joints: Residual Stress Effects
Incorporate residual stress measurements into CAE and correlate with test strains near welds, assessing the impact of residual stress on correlation.
CorrelationResidual
24
Correlation of Rotating Machinery: Order Tracking Analysis
Correlate CAE order-tracked responses with test data from run-up/down tests, and evaluate critical speed predictions.
CorrelationRotating
25
Correlation of Vehicle Dynamics: Handling Maneuvers
Correlate CAE vehicle dynamics simulations with test data from standard maneuvers (e.g., step steer), using metrics like yaw rate error and lateral acceleration.
CorrelationDynamics
26
Correlation of Crash Simulations: Occupant Response
Correlate CAE crash pulses and occupant injury criteria with sled test data, and compute correlation metrics for acceleration and force time histories.
CorrelationSimulations
27
Correlation of Aeroelasticity: Flutter Boundary Prediction
Correlate CAE aeroelastic predictions with wind tunnel test data by comparing flutter boundaries and damping trends.
CorrelationAeroelasticity
28
Correlation of Multibody Systems: Joint Clearance Effects
Correlate CAE multibody simulations with test data from a mechanism with joint clearances, and quantify the effect of clearance on correlation.
CorrelationMultibody
29
Automated Correlation Reporting: Generating CORA Scorecards
Develop a script to automate the computation of CORA scores for multiple signals and generate a summary report with pass/fail criteria.
AutomatedCorrelation
30
Correlation Case Study: End-to-End Validation of a Subsystem
Execute a complete correlation study for a subsystem, from data acquisition to final CORA assessment, and document lessons learned and recommendations.
CorrelationEnd-to-End